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On polychoric and polyserial partial correlation coefficients: a Bayesian approach

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  • Hikaru Hasegawa

Abstract

This article provides the estimation method for multivariate polychoric and polyserial correlation coefficients by using the simulation-based Bayesian method. It also shows that the partial version of the polychoric and polyserial correlation coefficients can be estimated using the corresponding estimates of the simple version. A simulation study illustrates the proposed method. Further, an application of the method to subjective well-being data is provided. Copyright Sapienza Università di Roma 2013

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  • Hikaru Hasegawa, 2013. "On polychoric and polyserial partial correlation coefficients: a Bayesian approach," METRON, Springer;Sapienza Università di Roma, vol. 71(2), pages 139-156, September.
    • Handle: RePEc:spr:metron:v:71:y:2013:i:2:p:139-156
    DOI: 10.1007/s40300-013-0012-1
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    1. Wai-Yin Poon & Sik-Yum Lee, 1987. "Maximum likelihood estimation of multivariate polyserial and polychoric correlation coefficients," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 409-430, September.
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    1. Hikaru Hasegawa & Kazuhiro Ueda, 2016. "Multidimensional inequality for current status of Japanese private companies’ employees," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 357-373, December.

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